Difference between revisions of "Sampling with GPS-enabled smartphone and DII"

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Between 2015 and 2017 a team of researchers involved in the projects MOD-CO and GFBio established a praxis-oriented workflow for ecological research groups. The field ecologist should be enabled for effective sampling environmental vouchers. The proposed procedure is generic, effective and basically independent from data management solutions or specific collection management systems. The DWB team was involved in software design and implementation of a new tool, called DiversityImageInspector.  
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Between 2015 and 2017 a team of researchers involved in the projects [http://www.mod-co.net/wiki/Main_Page MOD-CO] and [https://www.gfbio.org/ GFBio] worked on '''a best practice workflow for field ecologists'''. The aim was to enable researchers for effective sampling environmental vouchers with digital documentation of essential parameters already during the field campaign. The workflow established together with co-workers from Kenya and Algeria included the sampling with GPS-enabled smartphone and the set up of a generic, effective procedure which is basically independent from any data management solution or specific collection management system. The DWB team was involved in the design and implementation of the new data processing tool [[DiversityImageInspector]] '''(DII)''' which finally is generating CSV tables.  
  
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The results were published:
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The workflow described in [https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113 Triebel et al. (2018)] has 5 steps. The elements of step 1 to 4 (without data management in DWB databases) are visualised by [https://academic.oup.com/view-large/figure/108104585/bax096f1.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 1], [https://academic.oup.com/view-large/figure/108104588/bax096f2.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 2], [https://academic.oup.com/view-large/figure/108104595/bax096f3.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 3] and [https://academic.oup.com/view-large/figure/108104599/bax096f4.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 4].
  
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*Triebel, D., Reichert, W., Bosert, S., Feulner, M., Osieko Okach, D., Slimani, A. & Rambold, G. 2018. A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing. – Database, 2018 (Article ID bax096), 1–10. ([https://doi.org/10.1093/database/bax096 doi.org/10.1093/database/bax096]), see https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113.
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A closer view on workflow details is given below:
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The pages linked here give '''supplementary information''' on
  
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*[[Procedure for preparing UUID-QR-codes for labelling sampling containers|How to prepare UUID-QR-codes for labelling sampling containers]]
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*[[How to prepare UUID-QR-coded paper envelopes]]
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*[[How to select carrier types and use UUID-QR-coding of samples during analysis processes]]
  
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*'''Workflow (step 1 to step 3) demonstrated with images and a sample dataset'''
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Sample datasets from a research project in Africa ([http://www.kws.go.ke/content/ruma-national-park Ruma National Park]) with CSV table are deposited under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector '''(to be improuved)'''. This file (with import schema applied) is appropriate to be imported in [[DiversityCollection]], as visualised by [https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113 Triebel et al. (2018)], [https://academic.oup.com/view-large/figure/108104602/bax096f5.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 5] and [https://academic.oup.com/view-large/figure/108104603/bax096f6.tif/generic%20workflow%20for%20effective%20sampling%20of%20environmental%20vouchers%20with%20UUID%20assignment%20and%20image%20processing Fig. 6].
  
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[[Procedure for preparing UUID-QR-codes for labelling sampling containers]]
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with generation of UUID-QR-codes, image processing (see wiki site below, to be done)
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Reference:
  
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*Triebel, D., Reichert, W., Bosert, S., Feulner, M., Osieko Okach, D., Slimani, A. & Rambold, G. 2018. A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing. – Database, 2018 (Article ID bax096), 1–10. ([https://doi.org/10.1093/database/bax096 doi.org/10.1093/database/bax096]), see https://academic.oup.com/database/article-abstract/doi/10.1093/database/bax096/4797113.
  
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*'''Workflow (step 4 to step 5, with DII involved) demonstrated with a sample dataset'''
 
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(to be done)
 
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Sample dataset (to be improved) as csv table under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector .
 
  
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This file (with import schema applied) is appropriate to be imported in DC.
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'''Back to [[Training materials ]]'''
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Latest revision as of 10:57, 23 January 2018

Between 2015 and 2017 a team of researchers involved in the projects MOD-CO and GFBio worked on a best practice workflow for field ecologists. The aim was to enable researchers for effective sampling environmental vouchers with digital documentation of essential parameters already during the field campaign. The workflow established together with co-workers from Kenya and Algeria included the sampling with GPS-enabled smartphone and the set up of a generic, effective procedure which is basically independent from any data management solution or specific collection management system. The DWB team was involved in the design and implementation of the new data processing tool DiversityImageInspector (DII) which finally is generating CSV tables.

The workflow described in Triebel et al. (2018) has 5 steps. The elements of step 1 to 4 (without data management in DWB databases) are visualised by Fig. 1, Fig. 2, Fig. 3 and Fig. 4.

The pages linked here give supplementary information on

Sample datasets from a research project in Africa (Ruma National Park) with CSV table are deposited under https://github.com/SNSB/DWB-Contrib/tree/master/DiversityCollection/Import/Schemas/DiversityImageInspector (to be improuved). This file (with import schema applied) is appropriate to be imported in DiversityCollection, as visualised by Triebel et al. (2018), Fig. 5 and Fig. 6.

Reference:



Back to Training materials

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